its a better random object
A better random number generator
A collection of utilities for better-auth
Get a random temporary file path
A lightweight set of components, focused on easy-of-use and performance.
Generate random numbers from various distributions.
Fastest random ID and random string generation for Node.js
TypeScript definitions for d3-random
Fastest UUIDv4 with good RNG
JSON.parse with context information on error
JSON.parse with context information on error
URL and cookie safe UIDs
Use the random function in CSS
The most comprehensive authentication framework for TypeScript.
An alias package for `crypto.randomBytes` in Node.js and/or browsers
Generate a cryptographically strong random string
Random utility functions for ethers.
Deterministic pseudo-random number generator for JavaScript and TypeScript
A better path.resolve() that normalizes paths on Windows
A better opn. Reuse the same tab on Chrome for 👨💻.
The fastest and simplest library for SQLite in Node.js.
Human-friendly JSON Schema validation for APIs
A Pulumi package to safely use randomness in Pulumi programs.
Telemetry package for Better Auth
This gem prints out random quotes that will make you design better.
Use the true random number service of RANDOM.ORG. The randomness comes from atmospheric noise, which for many purposes is better than the pseudo-random number algorithms typically used in computer programs.
Noisy sensor data, approximations in the equations that describe the system evolution, and external factors that are not accounted for all place limits on how well it is possible to determine the system's state. The Kalman filter deals effectively with the uncertainty due to noisy sensor data and to some extent also with random external factors. The Kalman filter produces an estimate of the state of the system as an average of the system's predicted state and of the new measurement using a weighted average. The purpose of the weights is that values with better (i.e., smaller) estimated uncertainty are "trusted" more. The weights are calculated from the covariance, a measure of the estimated uncertainty of the prediction of the system's state. The result of the weighted average is a new state estimate that lies between the predicted and measured state, and has a better estimated uncertainty than either alone. This process is repeated at every time step, with the new estimate and its covariance informing the prediction used in the following iteration. This means that the Kalman filter works recursively and requires only the last "best guess", rather than the entire history, of a system's state to calculate a new state.
Version 1.0.1 Update Notes: -Updated README "HOW TO RUN" -I'm not sure how to format this so it looks good on the gems website so please just see the README file. USE CASES: 1. Your friends bully you because your imaginary role playing worlds are predictable and boring. 2. You like seeing chars printed in nifty patterns. HOW TO RUN: 1. Run `super_simple_world_builder` 2. Follow the prompts EXAMPLE INPUT: Guten Tag! Welcome to Super Simple World Builder. Enter 1 to build a random world Enter 2 to build a custom world Please enter your selection (1, 2, or exit): 2 Enter the name of your world: Community-Town Enter the minimum width of the world: 15 Enter the minimum height of the world: 15 What character do you want to fill the background of your world with? (i.e. any character or single space) How many lake features do you want? 3 How many mountain features do you want? 2 How many town features do you want? 3 How many forest features do you want? 4 OUTPUT: 1. Console print out of the world map 2. A text file of the world map ACHTUNG: 1. Don't worry if the width or height entered is too small. The world will automatically enlarge to fit all features. 2. World maps look better when you enter a <space> as the character to fill the background. 3. This is a quick-and-dirty project so yolo with the specs. I added comments as a consolation prize. 4. See `feature_set.rb` to tweak the features that can be added to the world map. 5. Interestingly, menu prompts may not show up in the git bash terminal. But they do show up in Windows command prompt, so lmao. 6. Feel free to tweak the code however you like. I plan to refactor in the future to dry up some sections.
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